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Autoware Documentation

Home
Home
- Vision, Mission, and Core Values
- Roadmap
  Roadmap
  - Timelines
    Timelines
    Humble to Jazzy
    Point cloud type transition
  - Autoware Multi-Year Roadmap
Installation
Installation
- Autoware
  Autoware
  - Open AD Kit: Containerized workloads for Autoware
  - Source installation
- Related tools
  Related tools
- Additional settings for developers
  Additional settings for developers
  - Console settings for ROS 2
  - Network configuration
    
    Network configuration
    DDS settings for ROS 2 and Autoware
    Zenoh settings for ROS 2 and Autoware
    Enable multicast on lo
    Communicating across multiple computers with CycloneDDS
Demos
Demos
- Digital twin demos
  Digital twin demos
  - AWSIM Full Demo
  - AWSIM with Autoware Core Demo
    
    AWSIM with Autoware Core Demo
  - MORAI Sim: Drive
  - CARLA simulator
  - PanoSim simulator demo
- Planning simulation
  Planning simulation
- Rosbag replay simulation
- Scenario simulation
  Scenario simulation
  - Scenario simulator
    Scenario simulator
    Installation
    Scenario test simulation
    Random test simulation
  - Driving Log Replayer
Tutorials
Tutorials
- Integrating Autoware
  Integrating Autoware
  - Overview
  - 1. Creating your Autoware repositories
    1. Creating your Autoware repositories
    Creating Autoware repositories
  - 2. Creating vehicle and sensor model
    
    2. Creating vehicle and sensor model
    
    Creating sensor model
    
    Creating sensor model
    
    Creating individual params
    
    Creating individual params
    
    Creating vehicle model
    
    Creating vehicle model
    
    Calibrating sensors
    
    Calibrating sensors
    
    Starting with TIER IV's CalibrationTools
    
    Starting with TIER IV's CalibrationTools
    
    Extrinsic manual calibration
    
    Extrinsic manual calibration
    
    Lidar-lidar calibration
    
    Lidar-lidar calibration
    
    Ground plane-lidar calibration
    
    Ground plane-lidar calibration
    
    Intrinsic camera calibration
    
    Intrinsic camera calibration
    
    Lidar-camera calibration
    
    Lidar-camera calibration
    
    Lidar-IMU calibration
    
    Lidar-IMU calibration
  - 3. Creating vehicle interface
    3. Creating vehicle interface
    Vehicle interface overview
    Creating vehicle interface
    Ackermann kinematic model
    Customizing for differential drive vehicle
  - 4. Creating maps
    
    4. Creating maps
    
    Open-source SLAM algorithms
    
    Open-source SLAM algorithms
    
    FAST-LIO-LC
    
    FAST-LIO-LC
    
    FAST_LIO_SLAM
    
    FAST_LIO_SLAM
    
    FD-SLAM
    
    FD-SLAM
    
    hdl_graph_slam
    
    hdl_graph_slam
    
    IA_LIO_SAM
    
    IA_LIO_SAM
    
    iscloam
    
    iscloam
    
    LeGO-LOAM-BOR
    
    LeGO-LOAM-BOR
    
    LIO-SAM
    
    LIO-SAM
    
    Optimized-SC-F-LOAM
    
    Optimized-SC-F-LOAM
    
    SC-A-LOAM
    
    SC-A-LOAM
    
    SC-LeGO-LOAM
    
    SC-LeGO-LOAM
    
    SLAM Algorithms Comparison
    
    SLAM Algorithms Comparison
    
    Converting UTM map to MGRS map
    
    Converting UTM map to MGRS map
    
    Pointcloud map preprocessing
    
    Pointcloud map preprocessing
    
    Creating a vector map
    
    Creating a vector map
    
    Lanelet2
    
    Lanelet2
    
    Crosswalk
    
    Crosswalk
    
    Stop line
    
    Stop line
    
    Traffic light
    
    Traffic light
    
    Speed bump
    
    Speed bump
    
    Detection area
    
    Detection area
  - 5. Launch Autoware
    
    5. Launch Autoware
    
    Launch vehicle
    
    Launch vehicle
    
    Launch system
    
    Launch system
    
    Launch map
    
    Launch map
    
    Launch sensing
    
    Launch sensing
    
    Launch localization
    
    Launch localization
    
    Eagleye
    
    Eagleye
    
    Launch perception
    
    Launch perception
    
    Launch planning
    
    Launch planning
    
    Launch control
    
    Launch control
  - 6. Tuning parameters and performance
    6. Tuning parameters and performance
    
    Sample tuning for campus environment
    
    Sample tuning for campus environment
    
    Tuning localization
    
    Tuning localization
    
    Tuning perception
    
    Tuning perception
    
    Tuning planning
    
    Tuning planning
    Evaluation
    Evaluation
    
    Evaluating the controller performance
    
    Evaluating the controller performance
    
    Evaluating real-time performance
    
    Evaluating real-time performance
  - 7. AWSIM Integration
    
    7. AWSIM Integration
  - 8. Integrating Sensors
    8. Integrating Sensors
    Integrating cameras
- Training Machine Learning Models
  Training Machine Learning Models
  - Training and Deploying Models
- Others
  Others
Architecture design
Architecture design
- Concepts
  Concepts
- Autoware system capabilities
- Architecture 1.0
  Architecture 1.0
  - Node diagram
    
    Node diagram
  - Components
    Components
    
    Sensing
    
    Sensing
    Data types
    Data types
    GNSS/INS data pre-processing design
    Image pre-processing design
    Point cloud pre-processing design
    Ultrasonics data pre-processing design
    Radar data
    Radar data
    Radar objects data pre-processing design
    Radar pointcloud data pre-processing design
    Reference implementations
    Reference implementations
    Data message for radars
    Device driver for radars
    
    Map
    
    Map
    Map requirements
    Map requirements
    
    Vector map requirements overview
    
    Vector map requirements overview
    Category area
    Category crosswalk
    Category intersection
    Category lane
    Category others
    Category stop line
    Category traffic light
    
    Localization
    
    Localization
    
    Perception
    
    Perception
    Perception Component Reference Implementation Design
    Reference implementations
    Reference implementations
    Radar based 3d detector
    Radar based 3d detector
    Radar faraway dynamic objects detection with radar objects
    Radar based 3D detector
    
    Planning
    
    Planning
    
    Control
    
    Control
    
    Vehicle
    
    Vehicle
  - Interfaces
    
    Interfaces
    
    AD API
    
    AD API
    Release notes
    
    List
    
    List
    
    Types
    
    Types
    Features
    Features
    Control
    Cooperation
    Diagnostics
    Fail-safe
    Heartbeat
    Interface
    Localization
    Manual control
    Motion
    Operation mode
    Perception
    Planning factors
    Routing
    Vehicle doors
    Vehicle status
    
    Components
    
    Components
    Planning
    Control
    Localization
    Map
    Sensing
    Perception
    Vehicle Interface
    Vehicle dimensions
- Architecture 2.0
  Architecture 2.0
  - Roadmap
    
    Roadmap
    Autonomous Driving Stack Architecture
    Detailed Architectural Interface
    Development Roadmap
    Neural World Simulation
    Assessment of Safety and Benchmarks
    Data, MLOps and Training
- Repository structure
- Repos files
- Versioning & release process
Reference design
Reference design
Simulation & Evaluation
Simulation & Evaluation
- Components evaluation
  Components evaluation
  - Localization evaluation
    Localization evaluation
    Urban environment evaluation
- Digital twin simulation
  Digital twin simulation
  - Compatibility test
Contributing
Contributing
- Open source philosophy
- License
- Coding guidelines
  Coding guidelines
  - Language-specific guidelines
    Language-specific guidelines
    C++
    Python
    Shell scripts
    Markdown
    CMake
    package.xml
    Docker
    GitHub Actions
  - ROS nodes guidelines
    ROS nodes guidelines
    Class design
    Console logging
    Coordinate system
    Directory structure
    Launch files
    Message guidelines
    Parameters
    Task scheduling
    Topic namespaces
    
    Topic message handling
    
    Topic message handling
    [supplement] Obtain a received message through intra-process communication
    [supplement] Use rclcpp::WaitSet
- Testing guidelines
  Testing guidelines
  - Unit testing
  - Integration testing
- Documentation guidelines
  Documentation guidelines
- Pull request guidelines
  Pull request guidelines
- Discussion guidelines
  Discussion guidelines
Datasets
Datasets
- Data Anonymization
  Data Anonymization
Community
Community
- Support
  Support
  - Support guidelines
  - Troubleshooting
    
    Troubleshooting
    Performance Troubleshooting
  - Docs guide
- Competitions
  Competitions

Network settings for ROS 2 and Autoware#

Single computer setup#

Multi computer setup#

Communicating across multiple computers with CycloneDDS